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Assessing the added predictive ability of a metabolic syndrome severity score in predicting incident cardiovascular disease and type 2 diabetes: the Atherosclerosis Risk in Communities Study and Jackson Heart Study.

ABSTRACT: Background:The severity of the metabolic syndrome (MetS) predicts future coronary heart disease (CHD) and diabetes independent of the individual MetS components. Our aim was to evaluate whether MetS severity conferred additional discrimination to existing scoring systems for cardiovascular disease (CVD) and diabetes risk. Methods:We assessed Cox proportional hazard models of CHD- and diabetes risk among 13,141 participants of the Atherosclerosis Risk in Communities Study and the Jackson Heart Study, using the Framingham Risk Calculator, the American Heart Association's Atherosclerotic CVD calculator, the American Diabetes Association diabetes risk score and an additional diabetes risk score derived from ARIC data. We then added a MetS-severity Z-score to these models and assessed for added risk discrimination by assessing Akaike information criterion, c-statistic, integrated discrimination improvement (IDI) and continuous net reclassification improvement (NRI). Results:The MetS severity score appears to add to the predictive ability of individual CHD and diabetes risk scores. Using the IDI, MetS improved risk prediction for diabetes but not CHD risk. In all 4 scoring systems, MetS severity had a significant non-event NRI, improving the ability to exclude individuals without events. Assessing interactions between risk scores and MetS severity revealed that MetS severity was more highly associated with disease risk among those in the lowest quintiles of risk score, suggesting that MetS was particularly able to identify risk among individuals judged to be of low risk by existing algorithms. Conclusions:Mets severity improved prediction of diabetes more so than CHD. Incorporation of multiple risk predictors into electronic health records may help in better identifying those at high disease risk, who can then be placed earlier on preventative therapy.

SUBMITTER: Guo Y

PROVIDER: S-EPMC5956946 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Aims/hypothesisThe study aimed to assess for an association between the degree of severity of the metabolic syndrome and risk of type 2 diabetes beyond that conferred by the individual components of the metabolic syndrome.MethodsWe assessed HRs for an Adult Treatment Panel III (ATP-III) metabolic syndrome score (ATP-III MetS) and a sex- and race-specific continuous metabolic syndrome severity z score related to incident diabetes over a median of 7.8 years of follow-up among participants of two observational cohorts, the Atherosclerosis Risk in Communities study (n = 10,957) and the Jackson Heart Study (n = 2137).ResultsThe ATP-III MetS had an HR for incident diabetes of 4.36 (95% CI 3.83, 4.97), which was attenuated in models that included the individual metabolic syndrome components. By contrast, participants in the fourth quartile of metabolic syndrome severity (compared with the first quartile) had an HR of 17.4 (95% CI 12.6, 24.1) for future diabetes; in models that also included the individual metabolic syndrome components, this remained significant, with an HR of 3.69 (95% CI 2.42, 5.64). There was a race × metabolic syndrome interaction in these models such that HR was greater for black participants (5.30) than white participants (2.24). When the change in metabolic syndrome severity score was included in the hazard models, this conferred a further association, with changes in metabolic syndrome severity score of ≥0.5 having a HR of 2.66 compared with changes in metabolic syndrome severity score of ≤0.Conclusions/interpretationUse of a continuous sex- and race-specific metabolic syndrome severity z score provided an additional prediction of risk of diabetes beyond that of the individual metabolic syndrome components, suggesting an added risk conferred by the processes underlying the metabolic syndrome. Increases in this score over time were associated with further risk, supporting the potential clinical utility of following metabolic syndrome severity over time.

Project description:PurposeTo develop a new calcium score for use with unenhanced cardiac computed tomography (CT) that can be used to define the percentage of coronary arteries affected by calcium and to correlate this score with risk factors and cardiovascular events.Materials and methodsInstitutional review boards at all participating centers approved this HIPAA-compliant study, and all participants gave written informed consent. Calcium coverage score (CCS), which represents the percentage of coronary arteries affected by calcific plaque, was calculated for 3252 participants in the Multi-Ethnic Study of Atherosclerosis in whom calcific plaque was detected with CT. Quasi-Poisson models were used to estimate associations (assessed by using t tests with robust standard errors) between CCS and risk factors. Associations between the CCS, Agatston, and calcium mass scores (hereafter, mass scores) and outcomes were estimated and assessed by using Cox proportional hazards models with Wald tests. The predictive ability of these models was assessed by using area under the receiver operating characteristic curves and bootstrap t tests.ResultsAfter adjustments were made for age, race, ethnicity, and sex in the quasi-Poisson model, CCS was associated with hypertension, dyslipidemia, and diabetes (P < .001 for all diseases). After adjustments for age and sex, a twofold increase in CCS was associated with a 52% (95% confidence interval: 34%, 72%) increase in risk for any coronary heart disease (CHD) event. When Agatston or mass scores were included with CCS in a Cox model for prediction of CHD events, neither Agatston score nor mass score was a significant predictor, whereas CCS remained significantly associated with CHD events. Although receiver operating characteristic curves suggested that there was a difference between CCS score and Agatston and mass scores in prediction of a cardiac event, no differences in prediction of hard cardiac events (myocardial infarction, death) were found.ConclusionBoth spatial distribution and amount of calcified plaque contribute to risk for CHD.

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Assessing the added predictive ability of a metabolic syndrome severity score in predicting incident cardiovascular disease and type 2 diabetes: the Atherosclerosis Risk in Communities Study and Jackson Heart Study.

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